Neutron Reconstruction in the BM@N Experiment Using Machine Learning

Large distributed sensor arrays require repeated recalibration as radiation damage, material aging, gain variation, and readout drift alter channel responses. We studied a high-granularity calorimeter as a large sensor array and addressed unsupervised recalibration from two unpaired datasets: a nominal reference response and an aged response with attenuated cell-wise signals. Aging was modeled by a ...

Added: August 11, 2026

The Use of the Missing Sample Simulation Modeling to Create a Classification Model for Three or More Classes by the Example of the Carbohydrate Metabolism Disorder Degree Detection Problem

Новиков Р. С., Novopashin M., Pozin B., Programming and Computer Software 2026 Vol. 52 No. 1 P. 28 – 38

Added: June 26, 2026

Machine Learning Approach to Anticancer Activity Prediction of Transition-Metal Complexes Based on a Large-Scale Experimental Database

Krasnov L., Malikov D., Kiseleva M. et al., Journal of Medicinal Chemistry 2026 Vol. 69 No. 8 P. 8838–8851

In this work, we developed a straightforward data-driven approach to predict the cytotoxicity of metal complexes based entirely on their (metal + ligands) composition. To this end, we have manually curated MetalCytoToxDB─a comprehensive experimental database comprising 26,500 IC50 values for 7050 metal complexes against 754 cell lines from 1921 articles. Based on these, machine learning ...

Added: April 23, 2026

Особые экономические зоны Российской Федерации: моделирование решений потенциальных резидентов и процесса их генерации

Plesovskikh A., Journal of Applied Economic Research 2023 Т. 22 № 2 С. 323–354

Modern studies widely discuss the role of special economic zones in stimulating the economic growth and development of Russia, generating the necessary investment flows and increasing the country's innovative potential by expanding production in high-tech sectors of the economy with high added value. The purpose of the study is to model the process of generating ...

Added: April 13, 2026

Replacing Criterion of Creativity with Criterion of Investment for Results Created by Artificial Intelligence

Pakshin P., Legal Issues in the Digital Age 2026 Vol. 7 No. 1 P. 32–48

Artificial intelligence plays a significant role in automation, minimizing human intervention in fields such as medicine, art, and law. Despite the historically close relationship between art and technology, generative AI has expanded the potential for creative activity. A significant catalyst for this process has been the proliferation of pre-trained AI systems, which have accelerated the ...

Added: March 31, 2026

A Tool for Mass Generation of Random Step Environment Models with User-Defined Landscape Features

Gabdrahmanov R., Tsoy T., Martinez-Garcia E. et al., , in: Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - (Volume 1) ICINCO 2024.: SciTePress, 2024. P. 511–518.

Computer simulations are growing in popularity in robotics research due to their near-zero cost of error and lower labor intensity. One of necessary components of a simulation, in addition to a robot model, is a model of a world in which the robot operates. While it is always possible to construct a world model manually, ...

Added: March 17, 2026

Real-Bogus Classification for ZTF Data Releases: Two Approaches

Semenikhin T., Kornilov M., Pruzhinskaya M. et al., , in: 26th International Conference, DAMDID/RCDL 2024, Nizhny Novgorod, Russia, October 23–25, 2024, Revised Selected Papers. Data Analytics and Management in Data Intensive Domains. (CCIS, volume 2641).: Springer, 2026. P. 211–219.

We considered two fundamentally different approaches to real-bogus classification within the Zwicky Transient Facility survey data. The first approach is based on neural networks that take sequences of object images as input. The second approach uses features extracted from light curves and classical machine learning methods. Several models for both approaches were tested. Quality metrics ...

Added: March 11, 2026

Кластеризация паттернов потребления электроэнергии умного дома на основе ансамблевых методов машинного обучения

Maltseva S. V., Бериков В. Б., Кладов Д. Е. et al., В кн.: Информатика и прикладная математика: Материалы X Международной научно-практической конференции (08.10 - 11.10.2025 г.)Т. 1: Сборник материалов часть 1.: Алматы: Институт информационных и вычислительных технологий КН МНВО РК, 2025. С. 227–232.

This paper examines the problem of clustering consumption patterns for a private household. An ensemble algorithm based on the Wasserstein metric was developed and applied to cluster daily load profiles. The proposed approach allows for identifying typical energy consumption scenarios and interpreting consumer behavior. Results from computational experiments using real data are presented. ...

Added: March 3, 2026

Multimodal graph, surface, and language-based model for protein protein interaction prediction

Arteaga Moreano B. D., Chervov N., Poptsova M., Scientific Reports 2026 Vol. 16 No. 1 Article 4772

Accurate prediction of protein-protein interactions (PPIs) is fundamental to understanding biological processes and disease mechanisms. While deep learning offers a powerful alternative to costly experimental methods, existing approaches often overlook critical protein-surface information and rely on simplistic feature fusion techniques, thereby limiting performance. To address this, we introduce GSMFormer-PPI, a novel multimodal framework that integrates ...

Added: February 4, 2026

Refrigerant Leak Detection in Data Centers Using Topologically Determined Graph Neural Networks

Ivanov S., Borisov V., Ali S. et al., , in: 2025 IEEE XVII International Scientific and Technical Conference on Actual Problems of Electronic Instrument Engineering (APEIE).: IEEE, 2025. Ch. 127 P. 1–7.

This paper investigates the problem of detecting slow refrigerant leaks in a data center cooling system using a graph neural network. The study addresses the challenge of early fault identification, proposing a method for constructing a topological graph based on the engineering diagram, the physical layout, and the cause-and-effect relationships in the cooling system. This ...

Added: December 19, 2025

Method of Automated Dataset Collection for Microwave Filters Synthesis

Arinin O. V., Bakhmach D. M., Katsnelson A. et al., , in: 2025 Systems of Signals Generating and Processing in the Field of on Board Communications.: IEEE, 2025. P. 1–5.

This research discusses the method of dataset collection automatization for microwave filter synthesis by integrating machine learning techniques, thus reducing development time. Utilizing the 3D electromagnetic analysis software package, the study involves simulation and collecting geometric parameters and amplitude-frequency characteristics from three variants of passband highly selective microstrip tworesonator combined filters with stepped impedance resonators. ...

Added: December 6, 2025

Search for 𝐷0 meson decays to 𝜋+𝜋−𝑒+𝑒− and 𝐾+𝐾−𝑒+𝑒− final states

Aaij R., Abdelmotteleb A. S., Abellan Beteta C. et al., Physical Review D - Particles, Fields, Gravitation and Cosmology 2025 Vol. 111 No. 9 Article L091101

A search for 𝐷0 meson decays to the 𝜋+⁢𝜋−⁢𝑒+⁢𝑒− and 𝐾+⁢𝐾−⁢𝑒+⁢𝑒− final states is reported using a sample of proton-proton collisions collected by the LHCb experiment at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 6 fb−1. The decay 𝐷0 →𝜋+⁢𝜋−⁢𝑒+⁢𝑒− is observed for the first time when requiring that the two electrons are consistent with coming from the decay of a 𝜙 or 𝜌0/𝜔 meson. The ...

Added: December 4, 2025

Ultra Fast Warm Start Solution for Graph Recommendations

Yusupov V., Rakhuba M., Frolov E., , in: CIKM '25: Proceedings of the 34rd ACM International Conference on Information and Knowledge Management.: ACM, 2025. Ch. 1 P. 5469–5473.

In this work, we present a fast and effective Linear approach for updating recommendations in a scalable graph-based recommender system UltraGCN. Solving this task is extremely important to maintain the relevance of the recommendations under the conditions of a large amount of new data and changing user preferences. To address this issue, we adapt the ...

Added: October 3, 2025

Artificial Neural Networks and Machine Learning. ICANN 2025 International Workshops and Special Sessions: 34th International Conference on Artificial Neural Networks, Kaunas, Lithuania, September 9–12, 2025, Proceedings, Part V

Cham: Springer, 2025.

This book constitutes the refereed proceedings of 34th International Workshops which were held in conjunction with the 34th International Conference on Artificial Neural Networks and Machine Learning, ICANN 2025, held in Kaunas, Lithuania, September 9–12, 2025. The 20 full papers and 8 abstracts included in this workshop volume were carefully reviewed and selected from 42 submissions. ...

Added: September 29, 2025

ОТСЛЕЖИВАНИЕ РАЗВИТИЯ РАЗРУШЕНИЯ С ПОМОЩЬЮ КЛАСТЕРИЗАЦИИ ИМПУЛЬСОВ ТЕРМИЧЕСКИ СТИМУЛИРОВАННОЙ АКУСТИЧЕСКОЙ ЭМИССИИ ПРИ ОТСУТСТВИИ ЛОКАЦИИ

Индаков Г. С., Казначеев П. А., Майбук З. Я. et al., Геофизические исследования 2025 Т. 26 № 2 С. 99–124

The paper studies the clusterability of acoustic emission pulses during high-temperature heating of sandstone sample preliminarily subjected to mechanical loading. Mechanical loading was applied in uniaxial mode up to load close to destructive with appearance of signs of large cracks on the surface. After that, samples were subjected to thermal treatment up to 650 °C ...

Added: September 19, 2025

Rewriting the Rules: LLMs Vs. Traditional ML in University Admissions

Chepikov I., Karpov I., , in: 26th International Conference, AIED 2025, Palermo, Italy, July 22–26, 2025, Proceedings, Part I. Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium, Blue Sky, and WideAIED.: Springer, 2025. P. 352 – 358.

Modern LLM models such as BERT, ChatGPT, DeepSeek have shown great potential in solving various tasks, including text classification, text generation, analysis and summary of documents. In this paper, we show that these models close to classical ML approaches based on decision trees not only in text processing, but also in processing classical tabular data ...

Added: September 4, 2025

Production of protons, deuterons and tritons in argon-nucleus interactions at 3.2 A GeV

Afanasiev S., Agakishiev G., Aleksandrov A. et al., Journal of High Energy Physics (Германия) 2025 Vol. 2025 No. 8 Article 95

Results of the BM@N experiment at the Nuclotron/NICA complex on the production of protons, deuterons and tritons in interactions of an argon beam of 3.2 A GeV with fixed targets of C, Al, Cu, Sn and Pb are presented. Transverse mass spectra, rapidity distributions and multiplicities of protons, deuterons and tritons are measured. The results ...

Added: August 27, 2025

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics

Wien: Association for Computational Linguistics, 2025.

Added: August 26, 2025

Analysis of a Company Model in Conditions of Unstable Demand Using Reinforcement Learning Methods

Delev A., Semakov S., , in: 2025 8th International Conference on Artificial Intelligence and Big Data (ICAIBD).: IEEE, 2025. P. 318–322.

Profit is one of the most important economic indicators of a company’s performance, and for every company it is necessary to allocate resources in such a way as to obtain the maximum possible profit. The profit maximization problem is usually a dynamic optimization problem. This article discusses an approach to solving the production expansion problem ...

Added: August 25, 2025